scholarly journals Estimation of Translational Motion Parameters in Terahertz Interferometric Inverse Synthetic Aperture Radar (InISAR) Imaging Based on a Strong Scattering Centers Fusion Technique

2019 ◽  
Vol 11 (10) ◽  
pp. 1221 ◽  
Author(s):  
Ye Zhang ◽  
Qi Yang ◽  
Bin Deng ◽  
Yuliang Qin ◽  
Hongqiang Wang
Keyword(s):  
Synthetic Aperture Radar ◽  
Translational Motion ◽  
System Structure ◽  
Synthetic Aperture ◽  
Inverse Synthetic Aperture Radar ◽  
Motion Measurement ◽  
Scattering Centers ◽  
Motion Parameters ◽  
Strong Scattering ◽  
Aperture Radar

Translational motion of a target will lead to image misregistration in interferometric inverse synthetic aperture radar (InISAR) imaging. In this paper, a strong scattering centers fusion (SSCF) technique is proposed to estimate translational motion parameters of a maneuvering target. Compared to past InISAR image registration methods, the SSCF technique is advantageous in its high computing efficiency, excellent antinoise performance, high registration precision, and simple system structure. With a one-input three-output terahertz InISAR system, translational motion parameters in both the azimuth and height direction are precisely estimated. Firstly, the motion measurement curves are extracted from the spatial spectrums of mutually independent strong scattering centers, which avoids the unfavorable influences of noise and the “angle scintillation” phenomenon. Then, the translational motion parameters are obtained by fitting the motion measurement curves with phase unwrapping and intensity-weighted fusion processing. Finally, ISAR images are registered precisely by compensating the estimated translational motion parameters, and high-quality InISAR imaging results are achieved. Both simulation and experimental results are used to verify the validity of the proposed method.

scholarly journals Non-Stationary Platform Inverse Synthetic Aperture Radar Maneuvering Target Imaging Based on Phase Retrieval

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3333 ◽  
Author(s):  
Hongyin Shi ◽  
Saixue Xia ◽  
Qi Qin ◽  
Ting Yang ◽  
Zhijun Qiao
Keyword(s):  
Synthetic Aperture Radar ◽  
Phase Retrieval ◽  
Experimental Simulation ◽  
Synthetic Aperture ◽  
Retrieval Algorithm ◽  
Imaging Method ◽  
Inverse Synthetic Aperture Radar ◽  
Maneuvering Target ◽  
Motion Parameters ◽  
Aperture Radar

As a powerful signal processing tool for imaging moving targets, placing radar on a non-stationary platform (such as an aerostat) is a future direction of Inverse Synthetic Aperture Radar (ISAR) systems. However, more phase errors are introduced into the received signal due to the instability of the radar platform, making it difficult for popular algorithms to accurately perform motion compensation, which leads to severe effects in the resultant ISAR images. Moreover, maneuvering targets may have complex motion whose motion parameters are unknown to radar systems. To overcome the issue of non-stationary platform ISAR autofocus imaging, a high-resolution imaging method based on the phase retrieval principle is proposed in this paper. Firstly, based on the spatial geometric and echo models of the ISAR maneuvering target, we can deduce that the radial motion of the radar platform or the vibration does not affect the modulus of the ISAR echo signal, which provides a theoretical basis for the phase recovery theory for the ISAR imaging. Then, we propose an oversampling smoothness (OSS) phase retrieval algorithm with prior information, namely, the phase of the blurred image obtained by the classical imaging algorithm replaces the initial random phase in the original OSS algorithm. In addition, the size of the support domain of the OSS algorithm is set with respect to the blurred target image. Experimental simulation shows that compared with classical imaging methods, the proposed method can obtain the resultant motion-compensated ISAR image without estimating the radar platform and maneuvering target motion parameters, wherein the fictitious target is perfectly focused.

scholarly journals An Improved Space Debris ISAR Imaging Algorithm

2012 ◽  
Vol 6-7 ◽  
pp. 321-326
Author(s):  
Bao Ping Wang ◽  
Jun Jie Guo ◽  
Chao Sun
Keyword(s):  
Fourier Transform ◽  
Synthetic Aperture Radar ◽  
Space Debris ◽  
Position Error ◽  
Synthetic Aperture ◽  
Inverse Synthetic Aperture Radar ◽  
Imaging Algorithm ◽  
Scattering Centers ◽  
Isar Imaging ◽  
Aperture Radar

According to the Characteristics of space debris, single-range matching filtering (SRMF) can be used for space debris inverse synthetic aperture radar (ISAR) imaging. Combined SRMF and Coherent CLEAN algorithm can effectively solve high sidelobes problem brought by Fourier transform. However, when the SNR is low, the position error of scattering centers extracted by SRMF-CLEAN is big, and even some weak scatterings can’t be extracted. This paper uses Sequence CLEAN instead of Coherent CLEAN to availably solve the above problems. The experiment results confirm the validness of the proposed algorithm.

3D Imaging of Bistatic Inverse Synthetic Aperture Radar Based on the Factorization Method

2013 ◽  
Vol 347-350 ◽  
pp. 1091-1095
Author(s):  
Xin Wang ◽  
Chao Xuan Shang
Keyword(s):  
3D Reconstruction ◽  
Synthetic Aperture Radar ◽  
3D Imaging ◽  
Factorization Method ◽  
Synthetic Aperture ◽  
Inverse Synthetic Aperture Radar ◽  
Scattering Centers ◽  
Reconstruction Model ◽  
2D Images ◽  
Aperture Radar

Based on the geometrical projection of 3D scattering centers on the line of radar sight, a new method of bistatic inverse synthetic aperture radar 3D Imaging is proposed. In the method, Range-Doppler algorithm gives a sequence of 2D images of target during its motion, and 3D reconstruction of target geometry is completed by the factorization method. We analyzed the theory of Bi-ISAR 3D imaging, deduced the process of the factorization method, and introduced the hierarchical reconstruction model. The simulation verified the validity of the paper.

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